36 citations · 73 across the 30 of their papers we have counts for
31 papers
Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access
João Henrique Inacio de Souza, Mattia Merluzzi, Mateus P. Mota +2
Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channel coding and incur high latenc…
Game-Theoretic Latent Space Alignment for Multi-user Semantic MIMO Communications
Giuseppe Di Poce, Mattia Merluzzi, Emilio Calvanese Strinati +1
Semantic communications enable AI-native wireless systems by mapping raw data into compressed task-oriented latent representations. However, independently trained agents often rely…
Toward Integrated Sensing, Communications, and Edge Intelligence Networks
Mattia Merluzzi, Miltiadis C. Filippou, Paolo Di Lorenzo +1
Wireless systems are expanding their purposes, from merely connecting humans and things to connecting intelligence and opportunistically sensing of the environment through radio-fr…
Distributed Semantic Alignment over Interference Channels: A Game-Theoretic Approach
Giuseppe Di Poce, Mattia Merluzzi, Emilio Calvanese Strinati +1
Semantic communication acts as a key enabler for effective task execution in AI-driven systems, prioritizing the extraction of the underlying meaning before transmission. However,…
Towards Sustainable 6G: A Holistic View of Trade-offs and Enablers
Mattia Merluzzi, Olivier Bouchet, Ali Balador +9
The sixth generation of mobile networks (6G) can play a central role in shaping a sustainable future, the most compelling contemporary challenge. Connecting the unconnected, reduci…
Collaborative Edge Inference via Semantic Grouping under Wireless Channel Constraints
Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati
In this paper, we study the framework of collaborative inference, or edge ensembles. This framework enables multiple edge devices to improve classification accuracy by exchanging i…
Joint Channel and Semantic-aware Grouping for Effective Collaborative Edge Inference
Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati
We focus on collaborative edge inference over wireless, which enables multiple devices to cooperate to improve inference performance in the presence of corrupted data. Exploiting a…
Toward Energy and Location-Aware Resource Allocation in Next Generation Networks
Mandar Datar, Mattia Merluzzi
Wireless networks are evolving from radio resource providers to complex systems that also involve computing, with the latter being distributed across edge and cloud facilities. Als…
Adaptive Semantic Token Communication for Transformer-based Edge Inference
Alessio Devoto, Jary Pomponi, Mattia Merluzzi +2
This paper presents an adaptive framework for edge inference based on a dynamically configurable transformer-powered deep joint source channel coding (DJSCC) architecture. Motivate…
Balancing Costs and Utilities in Future Networks via Market Equilibrium with Externalities
Mandar Datar, Mattia Merluzzi
We study the problem of market equilibrium (ME) in future wireless networks, with multiple actors competing and negotiating for a pool of heterogeneous resources (communication and…
Goal-oriented Spectrum Sharing: Trading Edge Inference Power for Data Streaming Performance
Mattia Merluzzi, Miltiadis C. Filippou
We study the problem of spectrum sharing between goal-oriented (GO) and legacy data-oriented (DO) systems. For the former, data quality and representation is no longer optimized ba…
Semantic and Goal-oriented Wireless Network Coverage: The Area of Effectiveness
Mattia Merluzzi, Giuseppe Di Poce, Paolo Di Lorenzo
Assessing wireless coverage is a fundamental task for public network operators and private deployments, whose goal is to guarantee quality of service across the network while minim…
Goal-oriented Communications based on Recursive Early Exit Neural Networks
Jary Pomponi, Mattia Merluzzi, Alessio Devoto +3
This paper presents a novel framework for goal-oriented semantic communications leveraging recursive early exit models. The proposed approach is built on two key components. First,…
Optimizing RIS Impairments through Semantic Communication
Nour Hello, Mattia Merluzzi, Emilio Calvanese Strinati +1
This paper investigates how semantic communication can effectively influence and potentially redefine the limitations imposed by physical layer settings. Reconfigurable Intelligent…
Analyzing and Enhancing Queue Sampling for Energy-Efficient Remote Control of Bandits
Hiba Dakdouk, Mohamed Sana, Mattia Merluzzi
In recent years, the integration of communication and control systems has gained significant traction in various domains, ranging from autonomous vehicles to industrial automation…
Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach
Emilio Calvanese Strinati, Paolo Di Lorenzo, Vincenzo Sciancalepore +17
Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requir…
Enabling Edge Artificial Intelligence via Goal-oriented Deep Neural Network Splitting
Francesco Binucci, Mattia Merluzzi, Paolo Banelli +2
Deep Neural Network (DNN) splitting is one of the key enablers of edge Artificial Intelligence (AI), as it allows end users to pre-process data and offload part of the computationa…
Power Minimizing MEC Offloading with QoS Constraints over RIS-Empowered Communications
Mattia Merluzzi, Francesca Costanzo, Konstantinos D. Katsanos +2
This work lies at the intersection of two cutting edge technologies envisioned to proliferate in future 6G wireless systems: Multi-access Edge Computing (MEC) and Reconfigurable In…
Goal-oriented Communications for the IoT: System Design and Adaptive Resource Optimization
Paolo Di Lorenzo, Mattia Merluzzi, Francesco Binucci +4
Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and pr…
6G goal-oriented communications: How to coexist with legacy systems?
Mattia Merluzzi, Miltiadis C. Filippou, Leonardo Gomes Baltar +2
6G will connect heterogeneous intelligent agents to make them operate complex cooperative tasks. When connecting intelligence, two main research questions arise to identify how AI…
Lyapunov-Driven Deep Reinforcement Learning for Edge Inference Empowered by Reconfigurable Intelligent Surfaces
Kyriakos Stylianopoulos, Mattia Merluzzi, Paolo Di Lorenzo +1
In this paper, we propose a novel algorithm for energy-efficient, low-latency, accurate inference at the wireless edge, in the context of 6G networks endowed with reconfigurable in…
Blue Communications for Edge Computing: the Reconfigurable Intelligent Surfaces Opportunity
Fatima Ezzahra Airod, Mattia Merluzzi, Antonio Clemente +1
Wireless traffic is exploding, due to the myriad of new connections and the exchange of capillary data at the edge of the networks to operate real-time processing and decision maki…
Reconfigurable Intelligent Surface Aided Mobile Edge Computing over Intermittent mmWave Links
Fatima Ezzahra Airod, Mattia Merluzzi, Paolo Di Lorenzo +1
The advent of Reconfigurable Intelligent Surfaces (RISs) in wireless communication networks unlocks the way to support high frequency radio access (e.g. in millimeter wave) while o…
Energy-Efficient Dynamic Edge Computing with Electromagnetic Field Exposure Constraints
Mattia Merluzzi, Serge Bories, Emilio Calvanese Strinati
We present a dynamic resource allocation strategy for energy-efficient and Electromagnetic Field (EMF) exposure aware computation offloading at the wireless network edge. The goal…